[1]吴卓葵,何宏浩,张文峰,等.基于 Grey-Markov 的生鲜配送需求量预测系统[J].计算机技术与发展,2023,33(01):108-113.[doi:10. 3969 / j. issn. 1673-629X. 2023. 01. 017]
　WU Zhuo-kui,HE Hong-hao,ZHANG Wen-feng,et al.Design of Fresh Agricultural Products Distribution Demand PredictionSystem Based on Grey-Markov Model[J].,2023,33(01):108-113.[doi:10. 3969 / j. issn. 1673-629X. 2023. 01. 017]
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基于 Grey-Markov 的生鲜配送需求量预测系统()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
33
期数:
2023年01期
页码:
108-113
栏目:
软件技术与工程
出版日期:
2023-01-10

文章信息/Info

Title:
Design of Fresh Agricultural Products Distribution Demand PredictionSystem Based on Grey-Markov Model
文章编号:
1673-629X(2023)01-0108-06
作者:
吴卓葵1; 2 ; 何宏浩1 ; 张文峰1; 2 ; 张小花1; 2 ; 叶 祥1; 2
1. 仲恺农业工程学院 自动化学院,广东 广州 510225;
2. 广东省农产品冷链运输与物流工程技术研究中心,广东 广州 510225
Author(s):
WU Zhuo-kui1; 2 ; HE Hong-hao1 ; ZHANG Wen-feng1; 2 ; ZHANG Xiao-hua1; 2 ; YE Xiang1; 2
1. School of Automation,Zhongkai University of Agriculture and Engineering,Guangzhou 510225,China;
2. Guangdong Agricultural Products Cold Chain Transportation and Logistics Engineering Technology Research Center,Guangzhou 510225,China
关键词:
需求量预测; Grey-Markov; 配送; 生鲜农产品; C / S
Keywords:
demand prediction; Grey-Markov; distribution; fresh agricultural products; C / S
分类号:
TP311. 52
DOI:
10. 3969 / j. issn. 1673-629X. 2023. 01. 017
摘要:
对生鲜农产品配送需求量进行预测,实现按需配送,可以降低甚至实现生鲜农产品的零库存,减少生鲜农产品变质、腐烂等损耗。 为了高效预测生鲜农产品配送需求量,提出一种基于 Grey-Markov 的生鲜配送需求量预测系统。 系统以Grey-Markov 为预测模型,对生鲜农产品下一日的配送需求量进行预测,与指数回归等预测模型相比,Grey-Markov 模型具有更强的稳定性和更好的准确性。 系统设计采用 C / S 架构,实现以按需配送为目标的原始数据导入、原始数据管理、历史销量分析、需求量预测等功能。 详细介绍了系统的架构设计、功能设计、数据库设计和程序设计。 测试与应用结果表明,系统实现了预期的功能,应用效果良好,可有效减少生鲜农产品的损耗。 与使用系统前相比,日剩余未售出生鲜农产品总量可降低 20 百分点以上。
Abstract:
Predicting the distribution demand of fresh agricultural products can realize on-demand distribution which can reduce or evenrealize the zero inventory of fresh agricultural products and reduce the deterioration,decay and other losses of fresh agricultural products.In order to efficiently predict the distribution demand of fresh agricultural products, a fresh agricultural products distribution demandprediction system based on Grey-Markov model is proposed. The system takes Grey-Markov model as the prediction model to predictthe distribution demand of fresh agricultural products in the next day. Compared with the prediction models such as exponential regressionmodel,Grey-Markov model has stronger stability and better accuracy. The system adopts C / S architecture and realizes the functions oforiginal data import,original data management,historical sales analysis and demand prediction aimed at on-demand distribution. The architecture design,function design,database design and program design in such system are introduced in detail. The test and applicationresults show that such system realizes the expected function,with excellent application effect,and can effectively reduce the loss of freshagricultural products. Compared with before using the system,the total daily remaining unsold fresh agricultural products can decrease bymore than 20% .
更新日期/Last Update: 2023-01-10